{"schemaVersion":"jobsearcher.job.v1","id":"04635f4c03ceabfdda4edc26","url":"https://jobsearcher.com/jobs/04635f4c03ceabfdda4edc26","canonicalUrl":"https://jobsearcher.com/jobs/04635f4c03ceabfdda4edc26","title":"Data Tech Lead","description":"Data Tech Lead with AWS Experience: +12 YearsSkills: Data engineer, Python, AWS, Apache Spark, LambdaLocation: Fort Mill SCWe at Coforge are hiring Data Tech Lead with the following skill sets.Job DescriptionLead the design, development, and support of scalable enterprise data platforms using AWS cloud-native services and modern data engineering technologies. Guide Data Lake and Lakehouse implementation using Amazon S3, AWS Glue, Lake Formation, Athena, Postgres, Apache Iceberg, Delta Lake, and Parquet. Develop and review batch, incremental, and Change Data Capture pipelines for data from databases, APIs, files, enterprise applications, and streaming platforms. Build and optimize ETL and ELT workflows using AWS Glue, Apache Spark, PySpark, Python, SQL, Lambda, and distributed processing frameworks. Create reusable frameworks for ingestion, transformation, validation, reconciliation, exception handling, error recovery, and operational monitoring. Implement real-time and near-real-time processing using Kafka, Amazon MSK, Amazon Kinesis, Lambda, SNS, SQS, and EventBridge. Lead workflow orchestration using Apache Airflow, Amazon MWAA, AWS Step Functions, and event-based scheduling. Implement metadata, schema, catalog, lineage, and discovery capabilities using AWS Glue Data Catalog and Lake Formation. Improve performance and cost efficiency through partitioning, compaction, retention, lifecycle management, storage optimization, Spark tuning, and query optimization. Enforce data quality controls covering completeness, accuracy, consistency, integrity, uniqueness, and source-to-target reconciliation. Implement secure and governed access using IAM, KMS, S3 policies, Lake Formation permissions, encryption, and fine-grained controls.","company":"Coforge","rawCompany":"coforge","city":"Fort Mill","state":"SC","isRemote":false,"isActive":false,"createdAt":"2026-09-11T09:15:36.797Z","occupations":[{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"},{"code":"11-3021.00","title":"Computer and Information Systems Managers","slug":"computer-and-information-systems-managers"},{"code":"15-1243.00","title":"Database Architects","slug":"database-architects"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"518210","title":"Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services","slug":"computing-infrastructure-providers-data-processing-web-hosting-and-related-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Data Tech Lead","description":"Data Tech Lead with AWS Experience: +12 YearsSkills: Data engineer, Python, AWS, Apache Spark, LambdaLocation: Fort Mill SCWe at Coforge are hiring Data Tech Lead with the following skill sets.Job DescriptionLead the design, development, and support of scalable enterprise data platforms using AWS cloud-native services and modern data engineering technologies. Guide Data Lake and Lakehouse implementation using Amazon S3, AWS Glue, Lake Formation, Athena, Postgres, Apache Iceberg, Delta Lake, and Parquet. Develop and review batch, incremental, and Change Data Capture pipelines for data from databases, APIs, files, enterprise applications, and streaming platforms. Build and optimize ETL and ELT workflows using AWS Glue, Apache Spark, PySpark, Python, SQL, Lambda, and distributed processing frameworks. Create reusable frameworks for ingestion, transformation, validation, reconciliation, exception handling, error recovery, and operational monitoring. Implement real-time and near-real-time processing using Kafka, Amazon MSK, Amazon Kinesis, Lambda, SNS, SQS, and EventBridge. Lead workflow orchestration using Apache Airflow, Amazon MWAA, AWS Step Functions, and event-based scheduling. Implement metadata, schema, catalog, lineage, and discovery capabilities using AWS Glue Data Catalog and Lake Formation. Improve performance and cost efficiency through partitioning, compaction, retention, lifecycle management, storage optimization, Spark tuning, and query optimization. Enforce data quality controls covering completeness, accuracy, consistency, integrity, uniqueness, and source-to-target reconciliation. Implement secure and governed access using IAM, KMS, S3 policies, Lake Formation permissions, encryption, and fine-grained controls.","datePosted":"2026-09-11T09:15:36.797Z","dateModified":"2026-09-11T09:15:36.797Z","hiringOrganization":{"@type":"Organization","name":"Coforge","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Fort Mill","addressRegion":"SC","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"04635f4c03ceabfdda4edc26"},"url":"https://jobsearcher.com/jobs/04635f4c03ceabfdda4edc26"}}